Ponderada
Rafael Techio
2025-02-04
Carregamento e Preparação dos Dados
Carregamento dos Dados
InteliStatus <- read_csv("../../../../../../datasources-project/InteliStatus.csv")## Rows: 7245975 Columns: 3
## ── Column specification ────────────────────────────────────────────────────────
## Delimiter: ","
## chr (3): ID, STATUS, STATUS_DATA
##
## ℹ Use `spec()` to retrieve the full column specification for this data.
## ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message.InteliVeiculo <- read_csv("../../../../../../datasources-project/InteliVeiculo.csv")## Rows: 139707 Columns: 6
## ── Column specification ────────────────────────────────────────────────────────
## Delimiter: ","
## chr (6): ID, MODELL, FARBAU, FARBIN, ZIEL_LAND, PR
##
## ℹ Use `spec()` to retrieve the full column specification for this data.
## ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message.InteliResultados <- read_csv("../../../../../../datasources-project/InteliResultados.csv")## Rows: 1932313 Columns: 5
## ── Column specification ────────────────────────────────────────────────────────
## Delimiter: ","
## chr (5): ID, RESULT_ID, RESULT_DESCRIPTION, CAPTURE_TIME, STATUS
##
## ℹ Use `spec()` to retrieve the full column specification for this data.
## ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message.InteliFalhas <- read_csv("../../../../../../datasources-project/InteliFalhas.csv")## Rows: 679073 Columns: 12
## ── Column specification ────────────────────────────────────────────────────────
## Delimiter: ","
## chr (7): ID, DATA DETECCAO, PONTO, LOC, POS, TYPE_TEXT, COLUNA
## dbl (5): LOC_ID, POS_ID, TYPE_ID, VIEW_ID, LINHA
##
## ℹ Use `spec()` to retrieve the full column specification for this data.
## ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message.Inteli5Merges <- read.csv2("../../../../../../datasources-project/5-ids.csv", stringsAsFactors = FALSE)Visualização das primeiras Linhas
head(InteliStatus)## # A tibble: 6 × 3
## ID STATUS STATUS_DATA
## <chr> <chr> <chr>
## 1 2024-1422099 R210 2024-04-02-00.00.37.000000
## 2 2024-1422099 R212 2024-04-02-00.00.37.000000
## 3 2024-1431276 R213 2024-04-02-01.38.41.000000
## 4 2024-1431276 R215 2024-04-02-01.38.41.000000
## 5 2024-1452139 R300 2024-04-02-01.39.09.000000
## 6 2024-1422007 R213 2024-04-02-01.40.39.000000head(InteliVeiculo)## # A tibble: 6 × 6
## ID MODELL FARBAU FARBIN ZIEL_LAND PR
## <chr> <chr> <chr> <chr> <chr> <chr>
## 1 2024-1322010 R111Q4 B4B4 XK VY LRV:AV1 MSF:AW0 AUS:A8A BLB:B1D T…
## 2 2024-1332013 R111Q4 B4B4 XK VY LRV:AV1 MSF:AW0 AUS:A8A BLB:B1D T…
## 3 2024-1332022 R111Q4 B4B4 XK VY LRV:AV1 MSF:AW0 AUS:A8A BLB:B1D T…
## 4 2024-1332321 R111Q4 B4B4 XK VY LRV:AV1 MSF:AW0 AUS:A8A BLB:B1D T…
## 5 2024-1332322 R111Q4 B4B4 XK VY LRV:AV1 MSF:AW0 AUS:A8A BLB:B1D T…
## 6 2024-1332323 R111Q4 B4B4 XK VY LRV:AV1 MSF:AW0 AUS:A8A BLB:B1D T…head(InteliResultados)## # A tibble: 6 × 5
## ID RESULT_ID RESULT_DESCRIPTION CAPTURE_TIME STATUS
## <chr> <chr> <chr> <chr> <chr>
## 1 2024-3821101 53P007 ABASTEC. CÂMBIO 2019-02-14-08.20.57.000000 NOK
## 2 2024-3851264 53P007 ABASTEC. CÂMBIO 2019-02-14-08.31.27.000000 NOK
## 3 2024-3851264 53P007 ABASTEC. CÂMBIO 2019-02-14-08.31.57.000000 NOK
## 4 2024-3851264 53P007 ABASTEC. CÂMBIO 2019-02-14-08.33.57.000000 NOK
## 5 2024-3851264 53P007 ABASTEC. CÂMBIO 2019-02-14-08.34.27.000000 NOK
## 6 2024-3851264 53P007 ABASTEC. CÂMBIO 2019-02-14-08.34.57.000000 NOKhead(InteliFalhas)## # A tibble: 6 × 12
## ID `DATA DETECCAO` PONTO LOC_ID LOC POS_ID POS TYPE_ID TYPE_TEXT
## <chr> <chr> <chr> <dbl> <chr> <dbl> <chr> <dbl> <chr>
## 1 2024-3712154 2010-01-29-02.… RODA… 5.56e3 Tamp… -2 <NA> 70 "070 - R…
## 2 2024-3722068 2010-01-29-02.… RODA… 5.56e3 Tamp… -2 <NA> 70 "070 - R…
## 3 2024-3732080 2010-01-29-02.… RODA… 7.06e3 Reve… 5 dire… 70 "070 - R…
## 4 2024-3732079 2010-01-29-02.… RODA… 5.85e3 Port… 5 dire… 70 "070 - R…
## 5 2024-3711076 2010-01-29-02.… RODA… 4.66e3 Alav… -2 <NA> 5 "005 - B…
## 6 2024-3732094 2010-01-29-04.… RODA… 9.88e7 Regu… 3 esqu… 31 "031 - P…
## # ℹ 3 more variables: VIEW_ID <dbl>, COLUNA <chr>, LINHA <dbl>head(Inteli5Merges)## INTELI_FALHAS_DATA.DETECCAO INTELI_FALHAS_PONTO INTELI_FALHAS_LOC_ID
## 1 2024-10-30-00.20.10.000000 ZP7 5522
## 2 2024-10-30-00.20.10.000000 ZP7 5522
## 3 2024-10-30-00.20.10.000000 ZP7 5522
## 4 2024-10-30-00.20.10.000000 ZP7 5522
## 5 2024-10-30-00.20.10.000000 ZP7 5522
## 6 2024-10-30-00.20.10.000000 ZP7 5522
## INTELI_FALHAS_LOC INTELI_FALHAS_POS_ID INTELI_FALHAS_POS
## 1 Tampa dianteira 1 externo
## 2 Tampa dianteira 1 externo
## 3 Tampa dianteira 1 externo
## 4 Tampa dianteira 1 externo
## 5 Tampa dianteira 1 externo
## 6 Tampa dianteira 1 externo
## INTELI_FALHAS_TYPE_ID INTELI_FALHAS_TYPE_TEXT INTELI_FALHAS_VIEW_ID
## 1 124 124 - Cavaco 661.0
## 2 124 124 - Cavaco 661.0
## 3 124 124 - Cavaco 661.0
## 4 124 124 - Cavaco 661.0
## 5 124 124 - Cavaco 661.0
## 6 124 124 - Cavaco 661.0
## INTELI_FALHAS_COLUNA INTELI_FALHAS_LINHA INTELI_RESULTADOS_RESULT_ID
## 1 G 2.0 53TM2106
## 2 G 2.0 53TM2106
## 3 G 2.0 53TM2106
## 4 G 2.0 53TM2106
## 5 G 2.0 53TM2106
## 6 G 2.0 53TM2106
## INTELI_RESULTADOS_RESULT_DESCRIPTION INTELI_RESULTADOS_CAPTURE_TIME
## 1 210601 - Coxim do motor na longarina 2024-10-29-07.44.58.000000
## 2 210601 - Coxim do motor na longarina 2024-10-29-07.44.58.000000
## 3 210601 - Coxim do motor na longarina 2024-10-29-07.44.58.000000
## 4 210601 - Coxim do motor na longarina 2024-10-29-07.44.58.000000
## 5 210601 - Coxim do motor na longarina 2024-10-29-07.44.58.000000
## 6 210601 - Coxim do motor na longarina 2024-10-29-07.44.58.000000
## INTELI_RESULTADOS_STATUS INTELI_VEICULO_MODELL INTELI_VEICULO_FARBAU
## 1 NOK BZ32K3 B4B4
## 2 NOK BZ32K3 B4B4
## 3 NOK BZ32K3 B4B4
## 4 NOK BZ32K3 B4B4
## 5 NOK BZ32K3 B4B4
## 6 NOK BZ32K3 B4B4
## INTELI_VEICULO_FARBIN INTELI_VEICULO_ZIEL_LAND
## 1 WK VY
## 2 WK VY
## 3 WK VY
## 4 WK VY
## 5 WK VY
## 6 WK VY
## INTELI_VEICULO_PR
## 1 LRV:AV1 MSF:AW5 AUS:A8C BLB:B1D TPL:B41 RAD:CB1 MOT:DS8 ASG:EA0 ECO:EF0 ONL:EL0 MKE:EM0 RCO:EZ1 AAU:E0A FZS:F0A PAM:GP1 DFV:G02 GSP:G1A HAT:IA0 REI:I08 BAT:J1H KSU:KA0 KUH:KK1 KZB:KL0 BLE:KN0 KAR:K8G LEA:L0L GKV:L04 BGK:NY0 RUF:NZ0 SIB:N2E WIV:QG0 SPR:QH0 SEA:QI3 CHR:QJ1 KAS:QK0 TVE:QV0 VOS:Q1A SNR:S37 GMO:T26 ABA:UD0 AFH:UG1 ESS:U9C FHW:VF0 FGS:VL1 REL:V0A STV:0AS TUE:0A2 RST:0B1 FAD:0FR EDF:0ID ASY:0K0 SZU:0NW HIA:0N1 ZSS:0RZ SAU:0SH ZFM:0TA BTA:0VJ GKH:0YF KLZ:0Y7 UGH:00A BRS:1AS KRS:1A4 FRO:1C1 AHV:1D0 TYP:1EB AKB:1E7 RER:1G1 DFH:1JB BAH:1KA RAA:1NL LEN:1N1 ABR:1PA TWU:1SA BOW:1S1 AED:1TW VBK:1T2 KBX:1W0 ATA:1X0 BAV:1ZS KRM:1Z0 UEA:2A0 LSS:2C5 CWV:2D0 LRA:2FE CHA:2H0 STF:2JZ SWP:2UA SHI:2U4 FRI:2V1 ZKV:3B4 SHM:3C7 MIK:3D2 DEI:3FA LBH:3GA LER:3H0 KOV:3J4 SIE:3L1 BOB:3MJ HIS:3NB HAL:3P7 KOH:3Q6 GPR:3U1 GDM:3W5 SHA:3ZB TSV:4AP WSS:4GF TKV:4I3 SSH:4KC IRS:4L2 PBH:4P0 RSV:4QU FEH:4R4 AIB:4UF GNF:4U0 SAB:4X1 HAK:4Z4 GRV:5A8 KSA:5C0 TRF:5D1 LAC:5K0 EIH:5MA HGD:5N0 ASR:5RQ ASL:5SJ SON:5XH FEU:6A0 MAS:6E3 BBO:6FF DFO:6F2 KUG:6KA AWV:6K0 FLA:6LA GPS:6M0 HIM:6NA HBV:6PH SAG:6Q2 ASE:6YA AGM:7GX FVS:7G0 MFA:7J1 RDK:7K1 SNA:7L6 EIL:7M5 LOR:7P0 CDR:7QA NAV:7Q0 SLE:7R6 ESI:7W0 EPH:7X3 SPU:7Y0 GEN:8GG LIA:8G0 HSW:8IT FLS:8K1 HEW:8M1 SWS:8N4 LWR:8Q1 LSE:8RJ SBR:8SA LEL:8S2 NEL:8TA GRA:8T2 RAO:8UK NES:8WA WWA:8W0 SWR:8X0 SNH:8Y0 ANT:8ZG MKU:8Z4 HKA:9AB GRB:9E0 RAU:9JA INB:9MF SWZ:9PE SGK:9P9 EDW:9V6 AUD:9WG VTV:9ZX
## 2 LRV:AV1 MSF:AW5 AUS:A8C BLB:B1D TPL:B41 RAD:CB1 MOT:DS8 ASG:EA0 ECO:EF0 ONL:EL0 MKE:EM0 RCO:EZ1 AAU:E0A FZS:F0A PAM:GP1 DFV:G02 GSP:G1A HAT:IA0 REI:I08 BAT:J1H KSU:KA0 KUH:KK1 KZB:KL0 BLE:KN0 KAR:K8G LEA:L0L GKV:L04 BGK:NY0 RUF:NZ0 SIB:N2E WIV:QG0 SPR:QH0 SEA:QI3 CHR:QJ1 KAS:QK0 TVE:QV0 VOS:Q1A SNR:S37 GMO:T26 ABA:UD0 AFH:UG1 ESS:U9C FHW:VF0 FGS:VL1 REL:V0A STV:0AS TUE:0A2 RST:0B1 FAD:0FR EDF:0ID ASY:0K0 SZU:0NW HIA:0N1 ZSS:0RZ SAU:0SH ZFM:0TA BTA:0VJ GKH:0YF KLZ:0Y7 UGH:00A BRS:1AS KRS:1A4 FRO:1C1 AHV:1D0 TYP:1EB AKB:1E7 RER:1G1 DFH:1JB BAH:1KA RAA:1NL LEN:1N1 ABR:1PA TWU:1SA BOW:1S1 AED:1TW VBK:1T2 KBX:1W0 ATA:1X0 BAV:1ZS KRM:1Z0 UEA:2A0 LSS:2C5 CWV:2D0 LRA:2FE CHA:2H0 STF:2JZ SWP:2UA SHI:2U4 FRI:2V1 ZKV:3B4 SHM:3C7 MIK:3D2 DEI:3FA LBH:3GA LER:3H0 KOV:3J4 SIE:3L1 BOB:3MJ HIS:3NB HAL:3P7 KOH:3Q6 GPR:3U1 GDM:3W5 SHA:3ZB TSV:4AP WSS:4GF TKV:4I3 SSH:4KC IRS:4L2 PBH:4P0 RSV:4QU FEH:4R4 AIB:4UF GNF:4U0 SAB:4X1 HAK:4Z4 GRV:5A8 KSA:5C0 TRF:5D1 LAC:5K0 EIH:5MA HGD:5N0 ASR:5RQ ASL:5SJ SON:5XH FEU:6A0 MAS:6E3 BBO:6FF DFO:6F2 KUG:6KA AWV:6K0 FLA:6LA GPS:6M0 HIM:6NA HBV:6PH SAG:6Q2 ASE:6YA AGM:7GX FVS:7G0 MFA:7J1 RDK:7K1 SNA:7L6 EIL:7M5 LOR:7P0 CDR:7QA NAV:7Q0 SLE:7R6 ESI:7W0 EPH:7X3 SPU:7Y0 GEN:8GG LIA:8G0 HSW:8IT FLS:8K1 HEW:8M1 SWS:8N4 LWR:8Q1 LSE:8RJ SBR:8SA LEL:8S2 NEL:8TA GRA:8T2 RAO:8UK NES:8WA WWA:8W0 SWR:8X0 SNH:8Y0 ANT:8ZG MKU:8Z4 HKA:9AB GRB:9E0 RAU:9JA INB:9MF SWZ:9PE SGK:9P9 EDW:9V6 AUD:9WG VTV:9ZX
## 3 LRV:AV1 MSF:AW5 AUS:A8C BLB:B1D TPL:B41 RAD:CB1 MOT:DS8 ASG:EA0 ECO:EF0 ONL:EL0 MKE:EM0 RCO:EZ1 AAU:E0A FZS:F0A PAM:GP1 DFV:G02 GSP:G1A HAT:IA0 REI:I08 BAT:J1H KSU:KA0 KUH:KK1 KZB:KL0 BLE:KN0 KAR:K8G LEA:L0L GKV:L04 BGK:NY0 RUF:NZ0 SIB:N2E WIV:QG0 SPR:QH0 SEA:QI3 CHR:QJ1 KAS:QK0 TVE:QV0 VOS:Q1A SNR:S37 GMO:T26 ABA:UD0 AFH:UG1 ESS:U9C FHW:VF0 FGS:VL1 REL:V0A STV:0AS TUE:0A2 RST:0B1 FAD:0FR EDF:0ID ASY:0K0 SZU:0NW HIA:0N1 ZSS:0RZ SAU:0SH ZFM:0TA BTA:0VJ GKH:0YF KLZ:0Y7 UGH:00A BRS:1AS KRS:1A4 FRO:1C1 AHV:1D0 TYP:1EB AKB:1E7 RER:1G1 DFH:1JB BAH:1KA RAA:1NL LEN:1N1 ABR:1PA TWU:1SA BOW:1S1 AED:1TW VBK:1T2 KBX:1W0 ATA:1X0 BAV:1ZS KRM:1Z0 UEA:2A0 LSS:2C5 CWV:2D0 LRA:2FE CHA:2H0 STF:2JZ SWP:2UA SHI:2U4 FRI:2V1 ZKV:3B4 SHM:3C7 MIK:3D2 DEI:3FA LBH:3GA LER:3H0 KOV:3J4 SIE:3L1 BOB:3MJ HIS:3NB HAL:3P7 KOH:3Q6 GPR:3U1 GDM:3W5 SHA:3ZB TSV:4AP WSS:4GF TKV:4I3 SSH:4KC IRS:4L2 PBH:4P0 RSV:4QU FEH:4R4 AIB:4UF GNF:4U0 SAB:4X1 HAK:4Z4 GRV:5A8 KSA:5C0 TRF:5D1 LAC:5K0 EIH:5MA HGD:5N0 ASR:5RQ ASL:5SJ SON:5XH FEU:6A0 MAS:6E3 BBO:6FF DFO:6F2 KUG:6KA AWV:6K0 FLA:6LA GPS:6M0 HIM:6NA HBV:6PH SAG:6Q2 ASE:6YA AGM:7GX FVS:7G0 MFA:7J1 RDK:7K1 SNA:7L6 EIL:7M5 LOR:7P0 CDR:7QA NAV:7Q0 SLE:7R6 ESI:7W0 EPH:7X3 SPU:7Y0 GEN:8GG LIA:8G0 HSW:8IT FLS:8K1 HEW:8M1 SWS:8N4 LWR:8Q1 LSE:8RJ SBR:8SA LEL:8S2 NEL:8TA GRA:8T2 RAO:8UK NES:8WA WWA:8W0 SWR:8X0 SNH:8Y0 ANT:8ZG MKU:8Z4 HKA:9AB GRB:9E0 RAU:9JA INB:9MF SWZ:9PE SGK:9P9 EDW:9V6 AUD:9WG VTV:9ZX
## 4 LRV:AV1 MSF:AW5 AUS:A8C BLB:B1D TPL:B41 RAD:CB1 MOT:DS8 ASG:EA0 ECO:EF0 ONL:EL0 MKE:EM0 RCO:EZ1 AAU:E0A FZS:F0A PAM:GP1 DFV:G02 GSP:G1A HAT:IA0 REI:I08 BAT:J1H KSU:KA0 KUH:KK1 KZB:KL0 BLE:KN0 KAR:K8G LEA:L0L GKV:L04 BGK:NY0 RUF:NZ0 SIB:N2E WIV:QG0 SPR:QH0 SEA:QI3 CHR:QJ1 KAS:QK0 TVE:QV0 VOS:Q1A SNR:S37 GMO:T26 ABA:UD0 AFH:UG1 ESS:U9C FHW:VF0 FGS:VL1 REL:V0A STV:0AS TUE:0A2 RST:0B1 FAD:0FR EDF:0ID ASY:0K0 SZU:0NW HIA:0N1 ZSS:0RZ SAU:0SH ZFM:0TA BTA:0VJ GKH:0YF KLZ:0Y7 UGH:00A BRS:1AS KRS:1A4 FRO:1C1 AHV:1D0 TYP:1EB AKB:1E7 RER:1G1 DFH:1JB BAH:1KA RAA:1NL LEN:1N1 ABR:1PA TWU:1SA BOW:1S1 AED:1TW VBK:1T2 KBX:1W0 ATA:1X0 BAV:1ZS KRM:1Z0 UEA:2A0 LSS:2C5 CWV:2D0 LRA:2FE CHA:2H0 STF:2JZ SWP:2UA SHI:2U4 FRI:2V1 ZKV:3B4 SHM:3C7 MIK:3D2 DEI:3FA LBH:3GA LER:3H0 KOV:3J4 SIE:3L1 BOB:3MJ HIS:3NB HAL:3P7 KOH:3Q6 GPR:3U1 GDM:3W5 SHA:3ZB TSV:4AP WSS:4GF TKV:4I3 SSH:4KC IRS:4L2 PBH:4P0 RSV:4QU FEH:4R4 AIB:4UF GNF:4U0 SAB:4X1 HAK:4Z4 GRV:5A8 KSA:5C0 TRF:5D1 LAC:5K0 EIH:5MA HGD:5N0 ASR:5RQ ASL:5SJ SON:5XH FEU:6A0 MAS:6E3 BBO:6FF DFO:6F2 KUG:6KA AWV:6K0 FLA:6LA GPS:6M0 HIM:6NA HBV:6PH SAG:6Q2 ASE:6YA AGM:7GX FVS:7G0 MFA:7J1 RDK:7K1 SNA:7L6 EIL:7M5 LOR:7P0 CDR:7QA NAV:7Q0 SLE:7R6 ESI:7W0 EPH:7X3 SPU:7Y0 GEN:8GG LIA:8G0 HSW:8IT FLS:8K1 HEW:8M1 SWS:8N4 LWR:8Q1 LSE:8RJ SBR:8SA LEL:8S2 NEL:8TA GRA:8T2 RAO:8UK NES:8WA WWA:8W0 SWR:8X0 SNH:8Y0 ANT:8ZG MKU:8Z4 HKA:9AB GRB:9E0 RAU:9JA INB:9MF SWZ:9PE SGK:9P9 EDW:9V6 AUD:9WG VTV:9ZX
## 5 LRV:AV1 MSF:AW5 AUS:A8C BLB:B1D TPL:B41 RAD:CB1 MOT:DS8 ASG:EA0 ECO:EF0 ONL:EL0 MKE:EM0 RCO:EZ1 AAU:E0A FZS:F0A PAM:GP1 DFV:G02 GSP:G1A HAT:IA0 REI:I08 BAT:J1H KSU:KA0 KUH:KK1 KZB:KL0 BLE:KN0 KAR:K8G LEA:L0L GKV:L04 BGK:NY0 RUF:NZ0 SIB:N2E WIV:QG0 SPR:QH0 SEA:QI3 CHR:QJ1 KAS:QK0 TVE:QV0 VOS:Q1A SNR:S37 GMO:T26 ABA:UD0 AFH:UG1 ESS:U9C FHW:VF0 FGS:VL1 REL:V0A STV:0AS TUE:0A2 RST:0B1 FAD:0FR EDF:0ID ASY:0K0 SZU:0NW HIA:0N1 ZSS:0RZ SAU:0SH ZFM:0TA BTA:0VJ GKH:0YF KLZ:0Y7 UGH:00A BRS:1AS KRS:1A4 FRO:1C1 AHV:1D0 TYP:1EB AKB:1E7 RER:1G1 DFH:1JB BAH:1KA RAA:1NL LEN:1N1 ABR:1PA TWU:1SA BOW:1S1 AED:1TW VBK:1T2 KBX:1W0 ATA:1X0 BAV:1ZS KRM:1Z0 UEA:2A0 LSS:2C5 CWV:2D0 LRA:2FE CHA:2H0 STF:2JZ SWP:2UA SHI:2U4 FRI:2V1 ZKV:3B4 SHM:3C7 MIK:3D2 DEI:3FA LBH:3GA LER:3H0 KOV:3J4 SIE:3L1 BOB:3MJ HIS:3NB HAL:3P7 KOH:3Q6 GPR:3U1 GDM:3W5 SHA:3ZB TSV:4AP WSS:4GF TKV:4I3 SSH:4KC IRS:4L2 PBH:4P0 RSV:4QU FEH:4R4 AIB:4UF GNF:4U0 SAB:4X1 HAK:4Z4 GRV:5A8 KSA:5C0 TRF:5D1 LAC:5K0 EIH:5MA HGD:5N0 ASR:5RQ ASL:5SJ SON:5XH FEU:6A0 MAS:6E3 BBO:6FF DFO:6F2 KUG:6KA AWV:6K0 FLA:6LA GPS:6M0 HIM:6NA HBV:6PH SAG:6Q2 ASE:6YA AGM:7GX FVS:7G0 MFA:7J1 RDK:7K1 SNA:7L6 EIL:7M5 LOR:7P0 CDR:7QA NAV:7Q0 SLE:7R6 ESI:7W0 EPH:7X3 SPU:7Y0 GEN:8GG LIA:8G0 HSW:8IT FLS:8K1 HEW:8M1 SWS:8N4 LWR:8Q1 LSE:8RJ SBR:8SA LEL:8S2 NEL:8TA GRA:8T2 RAO:8UK NES:8WA WWA:8W0 SWR:8X0 SNH:8Y0 ANT:8ZG MKU:8Z4 HKA:9AB GRB:9E0 RAU:9JA INB:9MF SWZ:9PE SGK:9P9 EDW:9V6 AUD:9WG VTV:9ZX
## 6 LRV:AV1 MSF:AW5 AUS:A8C BLB:B1D TPL:B41 RAD:CB1 MOT:DS8 ASG:EA0 ECO:EF0 ONL:EL0 MKE:EM0 RCO:EZ1 AAU:E0A FZS:F0A PAM:GP1 DFV:G02 GSP:G1A HAT:IA0 REI:I08 BAT:J1H KSU:KA0 KUH:KK1 KZB:KL0 BLE:KN0 KAR:K8G LEA:L0L GKV:L04 BGK:NY0 RUF:NZ0 SIB:N2E WIV:QG0 SPR:QH0 SEA:QI3 CHR:QJ1 KAS:QK0 TVE:QV0 VOS:Q1A SNR:S37 GMO:T26 ABA:UD0 AFH:UG1 ESS:U9C FHW:VF0 FGS:VL1 REL:V0A STV:0AS TUE:0A2 RST:0B1 FAD:0FR EDF:0ID ASY:0K0 SZU:0NW HIA:0N1 ZSS:0RZ SAU:0SH ZFM:0TA BTA:0VJ GKH:0YF KLZ:0Y7 UGH:00A BRS:1AS KRS:1A4 FRO:1C1 AHV:1D0 TYP:1EB AKB:1E7 RER:1G1 DFH:1JB BAH:1KA RAA:1NL LEN:1N1 ABR:1PA TWU:1SA BOW:1S1 AED:1TW VBK:1T2 KBX:1W0 ATA:1X0 BAV:1ZS KRM:1Z0 UEA:2A0 LSS:2C5 CWV:2D0 LRA:2FE CHA:2H0 STF:2JZ SWP:2UA SHI:2U4 FRI:2V1 ZKV:3B4 SHM:3C7 MIK:3D2 DEI:3FA LBH:3GA LER:3H0 KOV:3J4 SIE:3L1 BOB:3MJ HIS:3NB HAL:3P7 KOH:3Q6 GPR:3U1 GDM:3W5 SHA:3ZB TSV:4AP WSS:4GF TKV:4I3 SSH:4KC IRS:4L2 PBH:4P0 RSV:4QU FEH:4R4 AIB:4UF GNF:4U0 SAB:4X1 HAK:4Z4 GRV:5A8 KSA:5C0 TRF:5D1 LAC:5K0 EIH:5MA HGD:5N0 ASR:5RQ ASL:5SJ SON:5XH FEU:6A0 MAS:6E3 BBO:6FF DFO:6F2 KUG:6KA AWV:6K0 FLA:6LA GPS:6M0 HIM:6NA HBV:6PH SAG:6Q2 ASE:6YA AGM:7GX FVS:7G0 MFA:7J1 RDK:7K1 SNA:7L6 EIL:7M5 LOR:7P0 CDR:7QA NAV:7Q0 SLE:7R6 ESI:7W0 EPH:7X3 SPU:7Y0 GEN:8GG LIA:8G0 HSW:8IT FLS:8K1 HEW:8M1 SWS:8N4 LWR:8Q1 LSE:8RJ SBR:8SA LEL:8S2 NEL:8TA GRA:8T2 RAO:8UK NES:8WA WWA:8W0 SWR:8X0 SNH:8Y0 ANT:8ZG MKU:8Z4 HKA:9AB GRB:9E0 RAU:9JA INB:9MF SWZ:9PE SGK:9P9 EDW:9V6 AUD:9WG VTV:9ZX
## ID INTELI_STATUS_STATUS INTELI_STATUS_STATUS_DATA
## 1 2024-4421153 A700 2024-10-21-06.31.58.000000
## 2 2024-4421153 R100 2024-10-26-03.09.05.000000
## 3 2024-4421153 R210 2024-10-26-04.02.22.000000
## 4 2024-4421153 R212 2024-10-26-04.02.22.000000
## 5 2024-4421153 R300 2024-10-27-17.17.46.000000
## 6 2024-4421153 R500 2024-10-28-10.32.39.000000Verificação da estrutura dos Dados
str(InteliStatus)## spc_tbl_ [7,245,975 × 3] (S3: spec_tbl_df/tbl_df/tbl/data.frame)
## $ ID : chr [1:7245975] "2024-1422099" "2024-1422099" "2024-1431276" "2024-1431276" ...
## $ STATUS : chr [1:7245975] "R210" "R212" "R213" "R215" ...
## $ STATUS_DATA: chr [1:7245975] "2024-04-02-00.00.37.000000" "2024-04-02-00.00.37.000000" "2024-04-02-01.38.41.000000" "2024-04-02-01.38.41.000000" ...
## - attr(*, "spec")=
## .. cols(
## .. ID = col_character(),
## .. STATUS = col_character(),
## .. STATUS_DATA = col_character()
## .. )
## - attr(*, "problems")=<externalptr>str(InteliVeiculo)## spc_tbl_ [139,707 × 6] (S3: spec_tbl_df/tbl_df/tbl/data.frame)
## $ ID : chr [1:139707] "2024-1322010" "2024-1332013" "2024-1332022" "2024-1332321" ...
## $ MODELL : chr [1:139707] "R111Q4" "R111Q4" "R111Q4" "R111Q4" ...
## $ FARBAU : chr [1:139707] "B4B4" "B4B4" "B4B4" "B4B4" ...
## $ FARBIN : chr [1:139707] "XK" "XK" "XK" "XK" ...
## $ ZIEL_LAND: chr [1:139707] "VY" "VY" "VY" "VY" ...
## $ PR : chr [1:139707] "LRV:AV1 MSF:AW0 AUS:A8A BLB:B1D TPL:B41 ASG:EA0 ECO:EF0 ONL:EL0 MKE:EM0 RCO:EZ1 AAU:E0A FZS:F0A PAM:GP0 GSP:G0C"| __truncated__ "LRV:AV1 MSF:AW0 AUS:A8A BLB:B1D TPL:B41 ASG:EA0 ECO:EF0 ONL:EL0 MKE:EM0 RCO:EZ1 AAU:E0A FZS:F0A PAM:GP0 GSP:G0C"| __truncated__ "LRV:AV1 MSF:AW0 AUS:A8A BLB:B1D TPL:B41 ASG:EA0 ECO:EF0 ONL:EL0 MKE:EM0 RCO:EZ1 AAU:E0A FZS:F0A PAM:GP0 GSP:G0C"| __truncated__ "LRV:AV1 MSF:AW0 AUS:A8A BLB:B1D TPL:B41 ASG:EA0 ECO:EF0 ONL:EL0 MKE:EM0 RCO:EZ1 AAU:E0A FZS:F0A PAM:GP0 GSP:G0C"| __truncated__ ...
## - attr(*, "spec")=
## .. cols(
## .. ID = col_character(),
## .. MODELL = col_character(),
## .. FARBAU = col_character(),
## .. FARBIN = col_character(),
## .. ZIEL_LAND = col_character(),
## .. PR = col_character()
## .. )
## - attr(*, "problems")=<externalptr>str(InteliResultados)## spc_tbl_ [1,932,313 × 5] (S3: spec_tbl_df/tbl_df/tbl/data.frame)
## $ ID : chr [1:1932313] "2024-3821101" "2024-3851264" "2024-3851264" "2024-3851264" ...
## $ RESULT_ID : chr [1:1932313] "53P007" "53P007" "53P007" "53P007" ...
## $ RESULT_DESCRIPTION: chr [1:1932313] "ABASTEC. CÂMBIO" "ABASTEC. CÂMBIO" "ABASTEC. CÂMBIO" "ABASTEC. CÂMBIO" ...
## $ CAPTURE_TIME : chr [1:1932313] "2019-02-14-08.20.57.000000" "2019-02-14-08.31.27.000000" "2019-02-14-08.31.57.000000" "2019-02-14-08.33.57.000000" ...
## $ STATUS : chr [1:1932313] "NOK" "NOK" "NOK" "NOK" ...
## - attr(*, "spec")=
## .. cols(
## .. ID = col_character(),
## .. RESULT_ID = col_character(),
## .. RESULT_DESCRIPTION = col_character(),
## .. CAPTURE_TIME = col_character(),
## .. STATUS = col_character()
## .. )
## - attr(*, "problems")=<externalptr>str(InteliFalhas)## spc_tbl_ [679,073 × 12] (S3: spec_tbl_df/tbl_df/tbl/data.frame)
## $ ID : chr [1:679073] "2024-3712154" "2024-3722068" "2024-3732080" "2024-3732079" ...
## $ DATA DETECCAO: chr [1:679073] "2010-01-29-02.25.25.000000" "2010-01-29-02.38.57.000000" "2010-01-29-02.44.54.000000" "2010-01-29-02.53.28.000000" ...
## $ PONTO : chr [1:679073] "RODAGEM" "RODAGEM" "RODAGEM" "RODAGEM" ...
## $ LOC_ID : num [1:679073] 5559 5559 7057 5851 4661 ...
## $ LOC : chr [1:679073] "Tampa traseira" "Tampa traseira" "Revestimento coluna A" "Porta traseira" ...
## $ POS_ID : num [1:679073] -2 -2 5 5 -2 3 3 5 4 3 ...
## $ POS : chr [1:679073] NA NA "direita" "direita" ...
## $ TYPE_ID : num [1:679073] 70 70 70 70 5 31 70 70 70 70 ...
## $ TYPE_TEXT : chr [1:679073] "070 - Ruído" "070 - Ruído" "070 - Ruído" "070 - Ruído" ...
## $ VIEW_ID : num [1:679073] NA NA NA NA NA NA NA NA NA NA ...
## $ COLUNA : chr [1:679073] NA NA NA NA ...
## $ LINHA : num [1:679073] NA NA NA NA NA NA NA NA NA NA ...
## - attr(*, "spec")=
## .. cols(
## .. ID = col_character(),
## .. `DATA DETECCAO` = col_character(),
## .. PONTO = col_character(),
## .. LOC_ID = col_double(),
## .. LOC = col_character(),
## .. POS_ID = col_double(),
## .. POS = col_character(),
## .. TYPE_ID = col_double(),
## .. TYPE_TEXT = col_character(),
## .. VIEW_ID = col_double(),
## .. COLUNA = col_character(),
## .. LINHA = col_double()
## .. )
## - attr(*, "problems")=<externalptr>str(Inteli5Merges)## 'data.frame': 368248 obs. of 23 variables:
## $ INTELI_FALHAS_DATA.DETECCAO : chr "2024-10-30-00.20.10.000000" "2024-10-30-00.20.10.000000" "2024-10-30-00.20.10.000000" "2024-10-30-00.20.10.000000" ...
## $ INTELI_FALHAS_PONTO : chr "ZP7" "ZP7" "ZP7" "ZP7" ...
## $ INTELI_FALHAS_LOC_ID : int 5522 5522 5522 5522 5522 5522 5522 5522 5522 5522 ...
## $ INTELI_FALHAS_LOC : chr "Tampa dianteira" "Tampa dianteira" "Tampa dianteira" "Tampa dianteira" ...
## $ INTELI_FALHAS_POS_ID : int 1 1 1 1 1 1 1 1 1 1 ...
## $ INTELI_FALHAS_POS : chr "externo" "externo" "externo" "externo" ...
## $ INTELI_FALHAS_TYPE_ID : int 124 124 124 124 124 124 124 124 124 124 ...
## $ INTELI_FALHAS_TYPE_TEXT : chr "124 - Cavaco" "124 - Cavaco" "124 - Cavaco" "124 - Cavaco" ...
## $ INTELI_FALHAS_VIEW_ID : chr "661.0" "661.0" "661.0" "661.0" ...
## $ INTELI_FALHAS_COLUNA : chr "G" "G" "G" "G" ...
## $ INTELI_FALHAS_LINHA : chr "2.0" "2.0" "2.0" "2.0" ...
## $ INTELI_RESULTADOS_RESULT_ID : chr "53TM2106" "53TM2106" "53TM2106" "53TM2106" ...
## $ INTELI_RESULTADOS_RESULT_DESCRIPTION: chr "210601 - Coxim do motor na longarina" "210601 - Coxim do motor na longarina" "210601 - Coxim do motor na longarina" "210601 - Coxim do motor na longarina" ...
## $ INTELI_RESULTADOS_CAPTURE_TIME : chr "2024-10-29-07.44.58.000000" "2024-10-29-07.44.58.000000" "2024-10-29-07.44.58.000000" "2024-10-29-07.44.58.000000" ...
## $ INTELI_RESULTADOS_STATUS : chr "NOK" "NOK" "NOK" "NOK" ...
## $ INTELI_VEICULO_MODELL : chr "BZ32K3 " "BZ32K3 " "BZ32K3 " "BZ32K3 " ...
## $ INTELI_VEICULO_FARBAU : chr "B4B4" "B4B4" "B4B4" "B4B4" ...
## $ INTELI_VEICULO_FARBIN : chr "WK" "WK" "WK" "WK" ...
## $ INTELI_VEICULO_ZIEL_LAND : chr "VY " "VY " "VY " "VY " ...
## $ INTELI_VEICULO_PR : chr "LRV:AV1 MSF:AW5 AUS:A8C BLB:B1D TPL:B41 RAD:CB1 MOT:DS8 ASG:EA0 ECO:EF0 ONL:EL0 MKE:EM0 RCO:EZ1 AAU:E0A FZS:F0A"| __truncated__ "LRV:AV1 MSF:AW5 AUS:A8C BLB:B1D TPL:B41 RAD:CB1 MOT:DS8 ASG:EA0 ECO:EF0 ONL:EL0 MKE:EM0 RCO:EZ1 AAU:E0A FZS:F0A"| __truncated__ "LRV:AV1 MSF:AW5 AUS:A8C BLB:B1D TPL:B41 RAD:CB1 MOT:DS8 ASG:EA0 ECO:EF0 ONL:EL0 MKE:EM0 RCO:EZ1 AAU:E0A FZS:F0A"| __truncated__ "LRV:AV1 MSF:AW5 AUS:A8C BLB:B1D TPL:B41 RAD:CB1 MOT:DS8 ASG:EA0 ECO:EF0 ONL:EL0 MKE:EM0 RCO:EZ1 AAU:E0A FZS:F0A"| __truncated__ ...
## $ ID : chr "2024-4421153" "2024-4421153" "2024-4421153" "2024-4421153" ...
## $ INTELI_STATUS_STATUS : chr "A700" "R100" "R210" "R212" ...
## $ INTELI_STATUS_STATUS_DATA : chr "2024-10-21-06.31.58.000000" "2024-10-26-03.09.05.000000" "2024-10-26-04.02.22.000000" "2024-10-26-04.02.22.000000" ...Resumo Estatístico e Descrição dos Dados
Resumo estatístico
cat("\n\n\n===== Inteli Status =====\n\n\n")##
##
##
## ===== Inteli Status =====summary(InteliStatus)## ID STATUS STATUS_DATA
## Length:7245975 Length:7245975 Length:7245975
## Class :character Class :character Class :character
## Mode :character Mode :character Mode :charactercat("\n\n\n===== Inteli Veiculo =====\n\n\n")##
##
##
## ===== Inteli Veiculo =====summary(InteliVeiculo)## ID MODELL FARBAU FARBIN
## Length:139707 Length:139707 Length:139707 Length:139707
## Class :character Class :character Class :character Class :character
## Mode :character Mode :character Mode :character Mode :character
## ZIEL_LAND PR
## Length:139707 Length:139707
## Class :character Class :character
## Mode :character Mode :charactercat("\n\n\n===== Inteli Resultados =====\n\n\n")##
##
##
## ===== Inteli Resultados =====summary(InteliResultados)## ID RESULT_ID RESULT_DESCRIPTION CAPTURE_TIME
## Length:1932313 Length:1932313 Length:1932313 Length:1932313
## Class :character Class :character Class :character Class :character
## Mode :character Mode :character Mode :character Mode :character
## STATUS
## Length:1932313
## Class :character
## Mode :charactercat("\n\n\n===== Inteli Falhas =====\n\n\n")##
##
##
## ===== Inteli Falhas =====summary(InteliFalhas)## ID DATA DETECCAO PONTO LOC_ID
## Length:679073 Length:679073 Length:679073 Min. : 1001
## Class :character Class :character Class :character 1st Qu.: 5145
## Mode :character Mode :character Mode :character Median : 5559
## Mean : 3520407
## 3rd Qu.: 5851
## Max. :99008995
##
## LOC POS_ID POS TYPE_ID
## Length:679073 Min. : -2 Length:679073 Min. : 1
## Class :character 1st Qu.: 1 Class :character 1st Qu.: 39
## Mode :character Median : 10 Mode :character Median : 89
## Mean : 49464 Mean : 5766978
## 3rd Qu.: 17 3rd Qu.: 126
## Max. :9799976 Max. :99008934
##
## TYPE_TEXT VIEW_ID COLUNA LINHA
## Length:679073 Min. :661.0 Length:679073 Min. :1.00
## Class :character 1st Qu.:673.0 Class :character 1st Qu.:2.00
## Mode :character Median :689.0 Mode :character Median :3.00
## Mean :699.3 Mean :3.25
## 3rd Qu.:723.0 3rd Qu.:4.00
## Max. :778.0 Max. :6.00
## NA's :98563 NA's :98564cat("\n\n\n===== Inteli 5 Merges =====\n\n\n")##
##
##
## ===== Inteli 5 Merges =====summary(Inteli5Merges)## INTELI_FALHAS_DATA.DETECCAO INTELI_FALHAS_PONTO INTELI_FALHAS_LOC_ID
## Length:368248 Length:368248 Min. : 5000
## Class :character Class :character 1st Qu.: 5141
## Mode :character Mode :character Median : 5559
## Mean :16379
## 3rd Qu.: 6485
## Max. :70925
## INTELI_FALHAS_LOC INTELI_FALHAS_POS_ID INTELI_FALHAS_POS
## Length:368248 Min. : -1 Length:368248
## Class :character 1st Qu.: 1 Class :character
## Mode :character Median : 10 Mode :character
## Mean : 129663
## 3rd Qu.: 17
## Max. :9799949
## INTELI_FALHAS_TYPE_ID INTELI_FALHAS_TYPE_TEXT INTELI_FALHAS_VIEW_ID
## Min. : 4 Length:368248 Length:368248
## 1st Qu.: 23 Class :character Class :character
## Median : 87 Mode :character Mode :character
## Mean : 5818569
## 3rd Qu.: 126
## Max. :98721258
## INTELI_FALHAS_COLUNA INTELI_FALHAS_LINHA INTELI_RESULTADOS_RESULT_ID
## Length:368248 Length:368248 Length:368248
## Class :character Class :character Class :character
## Mode :character Mode :character Mode :character
##
##
##
## INTELI_RESULTADOS_RESULT_DESCRIPTION INTELI_RESULTADOS_CAPTURE_TIME
## Length:368248 Length:368248
## Class :character Class :character
## Mode :character Mode :character
##
##
##
## INTELI_RESULTADOS_STATUS INTELI_VEICULO_MODELL INTELI_VEICULO_FARBAU
## Length:368248 Length:368248 Length:368248
## Class :character Class :character Class :character
## Mode :character Mode :character Mode :character
##
##
##
## INTELI_VEICULO_FARBIN INTELI_VEICULO_ZIEL_LAND INTELI_VEICULO_PR
## Length:368248 Length:368248 Length:368248
## Class :character Class :character Class :character
## Mode :character Mode :character Mode :character
##
##
##
## ID INTELI_STATUS_STATUS INTELI_STATUS_STATUS_DATA
## Length:368248 Length:368248 Length:368248
## Class :character Class :character Class :character
## Mode :character Mode :character Mode :character
##
##
## Ajuste do Dataset
InteliStatus <- InteliStatus %>%
mutate(
ID = as.character(ID),
STATUS = as.factor(STATUS),
STATUS_DATA = as.POSIXct(STATUS_DATA, format="%Y-%m-%d-%H.%M.%S", tz="UTC")
)
InteliVeiculo <- InteliVeiculo %>%
mutate(
ID = as.character(ID),
MODELL = as.factor(MODELL),
FARBAU = as.factor(FARBAU),
FARBIN = as.factor(FARBIN),
ZIEL_LAND = as.factor(ZIEL_LAND),
PR = as.character(PR)
)
InteliResultados <- InteliResultados %>%
mutate(
ID = as.character(ID),
RESULT_ID = as.factor(RESULT_ID),
RESULT_DESCRIPTION = as.character(RESULT_DESCRIPTION),
CAPTURE_TIME = as.POSIXct(CAPTURE_TIME, format="%Y-%m-%d-%H.%M.%S", tz="UTC"),
STATUS = as.factor(STATUS)
)
InteliFalhas <- InteliFalhas %>%
mutate(
ID = as.character(ID),
`DATA DETECCAO` = as.POSIXct(`DATA DETECCAO`, format="%Y-%m-%d-%H.%M.%S", tz="UTC"),
PONTO=as.factor(PONTO),
LOC_ID=as.factor(LOC_ID),
LOC=as.factor(LOC),
POS_ID=as.factor(POS_ID),
POS=as.factor(POS),
TYPE_ID=as.factor(TYPE_ID),
TYPE_TEXT=as.factor(TYPE_TEXT),
VIEW_ID=as.factor(VIEW_ID),
COLUNA=as.factor(COLUNA),
LINHA=as.factor(LINHA)
)
Inteli5Merges <- Inteli5Merges %>%
mutate(
ID = as.character((ID)),
INTELI_STATUS_STATUS = as.factor(INTELI_STATUS_STATUS),
INTELI_STATUS_STATUS_DATA = as.POSIXct(INTELI_STATUS_STATUS_DATA, format="%Y-%m-%d-%H.%M.%S", tz="UTC"),
INTELI_VEICULO_MODELL = as.factor(INTELI_VEICULO_MODELL),
INTELI_VEICULO_FARBAU = as.factor(INTELI_VEICULO_FARBAU),
INTELI_VEICULO_FARBIN = as.factor(INTELI_VEICULO_FARBIN),
INTELI_VEICULO_ZIEL_LAND = as.factor(INTELI_VEICULO_ZIEL_LAND),
INTELI_VEICULO_PR = as.character(INTELI_VEICULO_PR),
INTELI_RESULTADOS_RESULT_ID = as.factor(INTELI_RESULTADOS_RESULT_ID),
INTELI_RESULTADOS_RESULT_DESCRIPTION = as.character(INTELI_RESULTADOS_RESULT_DESCRIPTION),
INTELI_RESULTADOS_CAPTURE_TIME = as.POSIXct(INTELI_RESULTADOS_CAPTURE_TIME, format="%Y-%m-%d-%H.%M.%S", tz="UTC"),
INTELI_RESULTADOS_STATUS = as.factor(INTELI_RESULTADOS_STATUS),
INTELI_FALHAS_PONTO=as.factor(INTELI_FALHAS_PONTO),
INTELI_FALHAS_LOC_ID=as.factor(INTELI_FALHAS_LOC_ID),
INTELI_FALHAS_LOC=as.factor(INTELI_FALHAS_LOC),
INTELI_FALHAS_POS=as.factor(INTELI_FALHAS_POS),
INTELI_FALHAS_TYPE_ID=as.factor(INTELI_FALHAS_TYPE_ID),
INTELI_FALHAS_TYPE_TEXT=as.factor(INTELI_FALHAS_TYPE_TEXT),
INTELI_FALHAS_VIEW_ID=as.factor(INTELI_FALHAS_VIEW_ID),
INTELI_FALHAS_COLUNA=as.factor(INTELI_FALHAS_COLUNA),
INTELI_FALHAS_LINHA=as.factor(INTELI_FALHAS_LINHA)
)Resumo estatístico corrigido
cat("\n\n\n===== Inteli Status =====\n\n\n")##
##
##
## ===== Inteli Status =====summary(InteliStatus)## ID STATUS STATUS_DATA
## Length:7245975 M690 : 151868 Min. :2024-04-02 00:00:37.00
## Class :character L790 : 142322 1st Qu.:2024-06-22 17:31:25.00
## Mode :character G700 : 139738 Median :2024-08-24 15:54:55.00
## G600 : 139731 Mean :2024-08-25 01:48:40.78
## G800 : 139725 3rd Qu.:2024-10-30 15:48:50.00
## G710 : 139723 Max. :2025-01-27 17:10:38.00
## (Other):6392868cat("\n\n\n===== Inteli Veiculo =====\n\n\n")##
##
##
## ===== Inteli Veiculo =====summary(InteliVeiculo)## ID MODELL FARBAU FARBIN ZIEL_LAND
## Length:139707 R111Q4 :70878 B4B4 :62141 WJ:17664 VY :110363
## Class :character BZ31T4 :19890 2R2R :31778 WK:22891 AR : 17415
## Mode :character BZ33K3 :13927 7Z7Z :26854 XK:99152 ME : 5550
## BZ32K3 : 8319 A1A1 :12312 KC : 2386
## BZ3SK3 : 7081 6K6K : 2421 VR : 1481
## R11SQ4 : 4201 B4A1 : 1846 BRA : 877
## (Other):15411 (Other): 2355 (Other): 1635
## PR
## Length:139707
## Class :character
## Mode :character
##
##
##
## cat("\n\n\n===== Inteli Resultados =====\n\n\n")##
##
##
## ===== Inteli Resultados =====summary(InteliResultados)## ID RESULT_ID RESULT_DESCRIPTION
## Length:1932313 53TM3201: 149066 Length:1932313
## Class :character 53TM6504: 143931 Class :character
## Mode :character 53TM2101: 136367 Mode :character
## 53TM3202: 131237
## 53TM6902: 110774
## 53TM3111: 97615
## (Other) :1163323
## CAPTURE_TIME STATUS
## Min. :2019-02-14 08:20:57 NOK:1932313
## 1st Qu.:2024-10-31 22:35:28
## Median :2024-11-25 08:13:39
## Mean :2024-11-15 17:58:16
## 3rd Qu.:2024-12-17 06:18:26
## Max. :2025-01-28 11:20:36
## cat("\n\n\n===== Inteli Falhas =====\n\n\n")##
##
##
## ===== Inteli Falhas =====summary(InteliFalhas)## ID DATA DETECCAO PONTO
## Length:679073 Min. :2010-01-29 02:25:25.00 ZP7 :530968
## Class :character 1st Qu.:2024-06-18 07:45:05.00 ZP5 : 59327
## Mode :character Median :2024-08-21 18:36:37.00 ZP6 : 28758
## Mean :2024-08-21 14:01:15.04 ZP5A : 28539
## 3rd Qu.:2024-10-29 03:29:09.00 RODAGEM: 10332
## Max. :2025-01-27 17:15:24.00 DKA_ZP8: 8259
## (Other): 12890
## LOC_ID LOC POS_ID
## 5559 :110595 Tampa traseira :110595 1 :189036
## 5751 : 76536 Porta dianteira : 76536 10 :159030
## 5851 : 76358 Porta traseira : 76358 17 :152265
## 5522 : 69613 Tampa dianteira : 69613 2 : 47415
## 5103 : 58266 Teto : 58266 -1 : 26634
## 5055 : 52672 Pára-lama dianteiro: 52672 3 : 19925
## (Other):235033 (Other) :235033 (Other): 84768
## POS TYPE_ID
## externo :189036 126 :119041
## direito externo :159030 4 : 83338
## esquerdo externo:152265 81 : 62723
## interno : 47415 125 : 29034
## * : 26634 73 : 27401
## (Other) : 93402 40 : 23022
## NA's : 11291 (Other):334514
## TYPE_TEXT VIEW_ID
## 126 - Sujeiras, contamina\\u00e7\\u00f5es:118154 661 : 67583
## 004 - Amassado : 83338 673 : 58861
## 081 - Caroço : 62723 665 : 56572
## 125 - Amassado (Montagem) : 29034 675 : 45160
## 073 - Sujo : 27401 715 : 36287
## 040 - Ajuste Incorreto : 23022 (Other):316047
## (Other) :335401 NA's : 98563
## COLUNA LINHA
## F :105788 1 : 53701
## G : 91272 2 :124516
## C : 89821 3 :152415
## B : 84715 4 :147095
## E : 80352 5 : 76596
## (Other):128487 6 : 26186
## NA's : 98638 NA's: 98564cat("\n\n\n===== Inteli 5 Merges =====\n\n\n")##
##
##
## ===== Inteli 5 Merges =====summary(Inteli5Merges)## INTELI_FALHAS_DATA.DETECCAO INTELI_FALHAS_PONTO INTELI_FALHAS_LOC_ID
## Length:368248 DKA_ZP8:104888 5559 : 56944
## Class :character ZP5 : 66560 5103 : 56144
## Mode :character ZP5A : 7224 51371 : 39184
## ZP7 :189576 5055 : 31472
## 5751 : 25592
## 53002 : 24856
## (Other):134056
## INTELI_FALHAS_LOC INTELI_FALHAS_POS_ID
## Tampa traseira : 56944 Min. : -1
## Teto : 56144 1st Qu.: 1
## Coluna A : 39184 Median : 10
## Pára-lama dianteiro : 31472 Mean : 129663
## Porta dianteira : 25592 3rd Qu.: 17
## Canal de escoamento de água: 24856 Max. :9799949
## (Other) :134056
## INTELI_FALHAS_POS INTELI_FALHAS_TYPE_ID
## externo :100272 4 : 54872
## direito externo : 82584 126 : 44568
## esquerdo externo: 79168 40 : 29624
## interno : 44344 144 : 25024
## * : 22456 73 : 23744
## esquerdo interno: 9968 87 : 23616
## (Other) : 29456 (Other):166800
## INTELI_FALHAS_TYPE_TEXT INTELI_FALHAS_VIEW_ID
## 004 - Amassado : 54872 : 62440
## 126 - Sujeiras, contamina\\u00e7\\u00f5es: 44568 665.0 : 56144
## 040 - Ajuste Incorreto : 29624 675.0 : 41880
## 144 - Sujeira de KTL : 25024 748.0 : 39184
## 073 - Sujo : 23744 689.0 : 24856
## 087 - Ponto de solda queimado/furado : 23616 661.0 : 23296
## (Other) :166800 (Other):120448
## INTELI_FALHAS_COLUNA INTELI_FALHAS_LINHA INTELI_RESULTADOS_RESULT_ID
## C :68024 :62440 53TM3201: 27520
## F :66624 1.0:46632 53TM2108: 26472
## :62440 2.0:84824 53TM6504: 25448
## G :56656 3.0:79840 53TM2101: 25000
## B :49720 4.0:57056 53TM3202: 24944
## D :35560 5.0: 9968 53TM6902: 19848
## (Other):29224 6.0:27488 (Other) :219016
## INTELI_RESULTADOS_RESULT_DESCRIPTION INTELI_RESULTADOS_CAPTURE_TIME
## Length:368248 Min. :2024-10-29 07:44:58.00
## Class :character 1st Qu.:2024-12-03 08:07:22.00
## Mode :character Median :2025-01-13 08:23:35.00
## Mean :2024-12-25 08:38:01.66
## 3rd Qu.:2025-01-17 10:46:01.00
## Max. :2025-01-27 15:55:50.00
##
## INTELI_RESULTADOS_STATUS
## NOK :277272
## NOK : 90976
##
##
##
##
##
## INTELI_VEICULO_MODELL INTELI_VEICULO_FARBAU INTELI_VEICULO_FARBIN
## BZ31T4 : 85120 2R2R: 60200 WK: 64400
## BZ32K3 : 64400 7Z7Z:179584 XK:303848
## BZ38Q4 : 94464 B4B4:128464
## R111Q4 :124264
##
##
##
## INTELI_VEICULO_ZIEL_LAND INTELI_VEICULO_PR ID
## AR : 42560 Length:368248 Length:368248
## ARG: 42560 Class :character Class :character
## BRA: 47232 Mode :character Mode :character
## VY :235896
##
##
##
## INTELI_STATUS_STATUS INTELI_STATUS_STATUS_DATA
## L402 : 11262 Min. :2024-10-21 06:30:48.00
## L412 : 11262 1st Qu.:2024-12-02 14:35:22.00
## L501 : 11187 Median :2025-01-14 06:31:17.00
## G600 : 8425 Mean :2024-12-23 06:36:37.51
## G605 : 8425 3rd Qu.:2025-01-17 10:57:59.00
## G630 : 8425 Max. :2025-01-27 17:10:38.00
## (Other):309262União de Datasets
Para fazer uma análise geral, de como os dados se unem entre si, foi identificada que a coluna ID presente em todos os datasets são correlacionáveis. Portanto, usando o google colab com recursos computacionais de nuvem, foram unidos os 5 ids que mais aparecem nos dados e que possuem registros em todas as tabelas, sendo o dataset Inteli5Merges
Descrição das variáveis
- InteliStatus: Contém informações sobre os status gerados pelas etapas de montagem.
- InteliVeiculo: Informações sobre os veículos como código geral da montadora.
- InteliResultados: Resultados de medições a partir de instrumentos de IOT.
- InteliFalhas: Registro de falhas identificadas durante as operações.
Inteli 5 Merges
Base criada através da união dos 5 IDs com mais registros em todas as tabelas. Feito para validar como os dados se relacionam e identificar correlações.
Análise Univariada
Visualização das distribuições
create_plots <- function(data, table_name) {
categorical_vars <- data %>%
select(where(is.factor)) %>%
colnames()
for (var in categorical_vars) {
p <- ggplot(data, aes_string(x = var)) +
geom_bar() +
theme_minimal() +
labs(title = paste("Distribuição de", var, "na tabela", table_name),
x = var, y = "Contagem")
print(p)
}
}Inteli Status
create_plots(InteliStatus, "InteliStatus")## Warning: `aes_string()` was deprecated in ggplot2 3.0.0.
## ℹ Please use tidy evaluation idioms with `aes()`.
## ℹ See also `vignette("ggplot2-in-packages")` for more information.
## This warning is displayed once every 8 hours.
## Call `lifecycle::last_lifecycle_warnings()` to see where this warning was
## generated.
Inteli Veiculo
create_plots(InteliVeiculo, "InteliVeiculo")
Inteli Resultados
create_plots(InteliResultados, "InteliResultados")
Inteli Falhas
create_plots(InteliFalhas, "InteliFalhas")
Inteli 5 Merges
create_plots(Inteli5Merges, "Inteli5Merges")
Identificação de outliers
create_barplot <- function(data, table_name) {
categorical_vars <- data %>%
select(where(is.factor)) %>%
colnames()
for (var in categorical_vars) {
# Contar a frequência de cada categoria
counts <- data %>%
count(.data[[var]], name = "frequency")
p <- ggplot(counts, aes(x = reorder(.data[[var]], -frequency), y = frequency)) +
geom_bar(stat = "identity", fill = "steelblue") +
geom_text(aes(label = frequency), size = 3, angle = 90) +
labs(
title = paste("Distribuição de", var, "na tabela", table_name),
x = var,
y = "Frequência"
) +
theme_minimal() +
theme(axis.text.x = element_text(angle = 90, hjust = 1)) # Rotaciona labels se houver muitas categorias
print(p)
}
}Inteli Status
create_barplot(InteliStatus, 'InteliStatus')
Inteli Veiculos
create_barplot(InteliVeiculo, "InteliVeiculo")
Inteli Resultados
create_barplot(InteliResultados, "InteliResultados")
Inteli Falhas
create_barplot(InteliFalhas, "InteliFalhas")
Inteli 5 Merges
create_barplot(Inteli5Merges, "Inteli5Merges")
Análise Bivariada
create_categorical_correlation_plot <- function(data, table_name) {
categorical_vars <- data %>%
select(where(is.factor))
var_names <- colnames(categorical_vars)
n <- length(var_names)
correlation_matrix <- matrix(0, nrow = n, ncol = n, dimnames = list(var_names, var_names))
for (i in 1:n) {
for (j in 1:n) {
if (i == j) {
correlation_matrix[i, j] <- 1
} else {
contingency_table <- table(categorical_vars[[i]], categorical_vars[[j]])
correlation_matrix[i, j] <- assocstats(contingency_table)$cramer
}
}
}
correlation_df <- as.data.frame(as.table(correlation_matrix)) %>%
rename(Var1 = Var1, Var2 = Var2, value = Freq)
p <- ggplot(correlation_df, aes(Var1, Var2, fill = value)) +
geom_tile() +
geom_text(aes(label = round(value, 2)), color = "black", size = 4) +
scale_fill_gradient2(low = "blue", mid = "white", high = "red", midpoint = 0.5, limits = c(0, 1)) +
labs(
title = paste("Correlação entre Variáveis Categóricas na Tabela", table_name),
x = NULL,
y = NULL,
fill = "V de Cramer"
) +
theme_minimal() +
theme(axis.text.x = element_text(angle = 45, hjust = 1))
print(p)
}Visualização de relações entre variáveis
Inteli Status
create_categorical_correlation_plot(InteliStatus, "InteliStatus")
Inteli Veiculo
create_categorical_correlation_plot(InteliVeiculo, "InteliVeiculo")
Inteli Resultados
create_categorical_correlation_plot(InteliResultados, "InteliResultados")## Warning: Removed 2 rows containing missing values or values outside the scale range
## (`geom_text()`).
Inteli Falhas
create_categorical_correlation_plot(InteliFalhas, "InteliFalhas")## Warning: Removed 46 rows containing missing values or values outside the scale range
## (`geom_text()`).
Inteli 5 Merges
create_categorical_correlation_plot(Inteli5Merges, "Inteli5Merges")
Análise Multivariada
Análise de Componentes Principais (PCA)
A análise de componentes principais (PCA) não é necessária nesse projeto, visto que não há features numéricas, sendo todas apenas categóricas ou descritivas.
Conclusão e Discussão
Sumário das Descobertas
- Nem todos os Ids aparecem em todas as tabelas
- A união dos dados gera um dataset gigantesco.
- Todos os status são NOK
- A base de veículos possui muitos dados de um modelo específico, e menos de outros
Discussão sobre Limitações e Possíveis Melhorias
Melhorar balanceamento dos dados
Melhorar estratégia de união dos dados usada, sumarizando status para uma análise detalhada